Data Background

Tables display data from sample 238 individuals from Sims data set that sustained a lower extremity injury within 1 year of sustaining a concussion. To include more data, the information below does not contain information from the merged IMPACT data sample.

Gender

Age at Concussion

Age at Second Injury

League

School

Sport Played Concussion Injury

Sport Level Concussion Injury

Sport Played Lower Extremity Injury

Sport Level Lower Extremity Injury

Second Injury Frequency

Table reflects 238 individuals from Sims data set with a diagnosed lower extremity injury following a concussion.

Duration of Time Between Concussion and Lower Extremity Injury

Gender

Summary Table

Descriptive statistics of time between concussion and lower extremity injury by gender

Box Plot

T-Test Results

## # A tibble: 1 x 9
##   .y.                 group1 group2    n1    n2 statistic    df     p p.signif
##   <chr>               <chr>  <chr>  <int> <int>     <dbl> <dbl> <dbl> <chr>   
## 1 days_between_injury Female Male      93   121     0.204  195. 0.838 ns

Age

Age Difference Distribution

To create plot, a new variable was created age_difference calculated as the difference between injury_2 age and injury_1 age. All differences are less than one year. The distribution is not normal with higher distribution at both tails.

Age 1 Total Distribution

Age 1 Distribution League

Age 1 Distribution Gender

Age 2 Total Distribution

Age 2 Distribution League

Age 2 Distribution Gender

Age Model

To produce the model, I calculated the relationship between the age at second injury and the days between injuries. There appears to be a significant relationship, although the model only accounts for 5% of the variance. Overall, there is a 31.339 unit increase in the days between injury for every unit increase in the age at time of 2nd injury.

## 
## Call:
## lm(formula = days_between_injury ~ age_2, data = age_diff)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -218.66 -102.28  -30.33  113.82  222.00 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -331.996    126.135  -2.632 0.009059 ** 
## age_2         31.339      7.973   3.931 0.000112 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 118.5 on 231 degrees of freedom
## Multiple R-squared:  0.06269,    Adjusted R-squared:  0.05863 
## F-statistic: 15.45 on 1 and 231 DF,  p-value: 0.000112

Sport

This section primarily explores the time between injuries for Football and Women’s Soccer as those are the two most common sports at time of concussion and lower extremity injury.

Descriptive Statistics

Table displayed statistics of the number of days between injuries for individuals who sustained their injuries playing football or women’s soccer.

Sport 2 Injury Type

Table displays the number of lower extremity injuries for individuals who played football and women’s soccer.

Box Plot

T-Test Results

## # A tibble: 1 x 9
##   .y.            group1  group2         n1    n2 statistic    df      p p.signif
##   <chr>          <chr>   <chr>       <int> <int>     <dbl> <dbl>  <dbl> <chr>   
## 1 days_between_… Footba… Women's So…    66    20     -1.80  28.6 0.0823 ns

School

Schools with 20 or more individuals included.

Descriptive Statistics

Table displayed statistics of the number of days between injuries for individuals who attend Kalaheo High School, Maui High School, and Mililani High Schol.

Boxplot

Anova

The difference between the mean number of days between injury across the three high schools is significantly different. Students at Mililani High School, on average, experienced a much longer duration of time between injuries than students at Kalaheo High School and Maui High School.

##             Df Sum Sq Mean Sq F value Pr(>F)  
## school_2     2 122006   61003   4.227 0.0188 *
## Residuals   65 938025   14431                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Pairwise Comparisons

## 
##  Pairwise comparisons using t tests with pooled SD 
## 
## data:  school_analysis$days_between_injury and school_analysis$school_2 
## 
##                      Kalaheo High School Maui High School
## Maui High School     1.000               -               
## Mililani High School 0.053               0.031           
## 
## P value adjustment method: bonferroni

Level

Schools with 20 or more individuals included.

Descriptive Statistics

Table displayed statistics of the number of days between injuries for the sport level at the time of the individuals’ lower extremity injury.

Box Plot

T-Test Results

Individuals playing varsity sports at the time of second injury have a significantly different longer duration of time between injuries.

## # A tibble: 1 x 9
##   .y.            group1      group2    n1    n2 statistic    df       p p.signif
##   <chr>          <chr>       <chr>  <int> <int>     <dbl> <dbl>   <dbl> <chr>   
## 1 days_between_… Junior Var… Varsi…    71   105     -3.48  165. 6.38e-4 ***

Days Missed Following Injuries

One individual removed from sample because of missing information for days since both injuries reducing sample total to 232 individauls. The number of days missed post-concussion appears to have severe outliers?

Descriptive Statistics

Days Missed Following Concussion

Days Missed Following Lower Extremity Injury

Days Missed Visualizations

Concussion Total

Concussion by Gender

Concussion by League

Concussion by Level

Lower Extremity Total

Lower Extremity by Gender

Lower Extremity by League

Lower Extremity by Level

T-Test Across Entire Sample

Boxplot

Results

## 
##  Paired t-test
## 
## data:  days_missed_1 and days_missed_2
## t = 1.1298, df = 231, p-value = 0.2597
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -41.55266 153.25955
## sample estimates:
## mean of the differences 
##                55.85345

Gender

Days Missed Following Concussion

Days Missed Following Lower Extremity Injury

Concussion Box Plot

Concussion T-Test Results

## # A tibble: 1 x 9
##   .y.                   group1 group2    n1    n2 statistic    df     p p.signif
##   <chr>                 <chr>  <chr>  <int> <int>     <dbl> <dbl> <dbl> <chr>   
## 1 days_missed_concussi… Female Male      92   121    -0.273  202. 0.785 ns

Lower Extremity Box Plot

Lower Extremity T-Test Results

## # A tibble: 1 x 9
##   .y.                  group1 group2    n1    n2 statistic    df      p p.signif
##   <chr>                <chr>  <chr>  <int> <int>     <dbl> <dbl>  <dbl> <chr>   
## 1 days_missed_lower_e… Female Male      92   121      1.90  143. 0.0594 ns

Age

There does not appear to be a strong relationship between age and the number of days missed following either a concussion or lower extremity injury.

Concussion

Lower Extremity Injury

Sport

This section primarily explores the number of days missed following injuries for Football and Women’s Soccer as those are the two most common sports at time of concussion and lower extremity injury.

Descriptive Statistics Concussion

Descriptive Statistics Lower Extremity Injury

Concussion Box Plot

Concussion T-Test Results

## # A tibble: 1 x 9
##   .y.             group1  group2        n1    n2 statistic    df      p p.signif
##   <chr>           <chr>   <chr>      <int> <int>     <dbl> <dbl>  <dbl> <chr>   
## 1 days_missed_co… Footba… Women's S…    66    19      1.87  74.9 0.0655 ns

Lower Extremity Box Plot

Lower Extremity T-Test Results

## # A tibble: 1 x 9
##   .y.              group1  group2        n1    n2 statistic    df     p p.signif
##   <chr>            <chr>   <chr>      <int> <int>     <dbl> <dbl> <dbl> <chr>   
## 1 days_missed_low… Footba… Women's S…    66    19    -0.868  21.2 0.395 ns